CubeSat missions demand continuous monitoring of onboard subsystems to ensure mission reliability and prevent catastrophic failures caused by abnormal operating conditions. Parameters such as temperature variations, gas leakage, pressure imbalance, and orientation misalignment can significantly affect satellite performance if not detected at an early stage. This project presents the design and development of an Autonomous Multi-Sensor Health Management Architecture for CubeSat Onboard Computers, implemented as a ground-based prototype to simulate real-time satellite telemetry and diagnostics. The proposed system integrates multiple sensors, including temperature, pressure, gas, and inertial measurement units, interfaced with microcontroller platforms such as Raspberry Pi Pico H and Arduino UNO R4 Wi-Fi. Real-time telemetry data is acquired, processed, and transmitted to a ground monitoring interface for visualization and analysis. The system employs threshold-based and trend-based analysis techniques to detect anomalies and log faults with accurate timestamps for further diagnostics. This prototype demonstrates an effective and compact health monitoring framework that enhances fault detection capability, improves situational awareness, and supports proactive maintenance strategies for CubeSat missions. The results validate the suitability of the proposed architecture for future onboard implementation, contributing to improved mission safety, reliability, and operational efficiency in small satellite systems.

The Autonomous Multi-Sensor Health Monitoring and Telemetry System for CubeSat Onboard Computers was successfully designed, implemented, and validated using a ground-based prototype. The system continuously monitored critical parameters such as temperature, pressure, gas concentration, and orientation, providing real-time insight into the operational health of the CubeSat subsystem. Multi- sensor integration and embedded processing enabled accurate data acquisition, effective fault detection, and reliable telemetry transmission to the ground monitoring interface. The system operated autonomously without the need for continuous human intervention, reducing dependency on ground station communication. Testing and validation results confirmed stable performance, reliable fault logging, and consistent telemetry delivery under various operating conditions. The proposed architecture is cost-effective, scalable, and well suited for CubeSat and small satellite applications, and it provides a strong foundation for future enhancements and real-time space mission implementation.

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